#' Simulated Pharmacometric Data
#'
#' A fictitious dataset giving doses and pharmacometric samples for multiple subjects in an imaginary Phase * drug trial.
#'
#' @format A data frame with 600 rows and 24 variables:
#' \describe{
#' \item{C}{a comment flag, typically NA but 'C' for records that should be ignored}
#' \item{ID}{integer subject identifier}
#' \item{TIME}{relative time (h)}
#' \item{SEQ}{sequence identifier to break ties when sorting}
#' \item{EVID}{event type identifier, 0: pk sample, 1: dose}
#' \item{AMT}{drug amount (mg)}
#' \item{DV}{plasma drug concentration (ng/mL)}
#' \item{SUBJ}{subject identifier}
#' \item{HOUR}{nominal hour (h)}
#' \item{HEIGHT}{height (cm)}
#' \item{WEIGHT}{weight (kg)}
#' \item{SEX}{sex, 0: female, 1: male}
#' \item{AGE}{age (y)}
#' \item{DOSE}{dose group (mg)}
#' \item{FED}{prandial state, 0: fasted, 1: fed}
#' \item{SMK}{smoker status, 0: non, 1: smoker}
#' \item{DS}{disease state, 0: no disease}
#' \item{CRCN}{normalized creatinine clearance (mL/min)}
#' \item{TAFD}{time since first dose (h)}
#' \item{TAD}{time since most recent dose (h)}
#' \item{LDOS}{amount of most recent dose (mg)}
#' \item{MDV}{missing dependent value, 0: not missing, 1: missing}
#' \item{predose}{predose flag, 0: record not predose, 1: record is predose}
#' \item{zerodv}{zero DV flag, 0, DV not zero, 1: DV is zero}
#' }
"drug"
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